LFD Book Forum Spatial visualization in more than 3 dimensions
 Register FAQ Calendar Mark Forums Read

#1
07-26-2012, 09:33 PM
 Ubermensch Junior Member Join Date: Jun 2012 Posts: 4
Spatial visualization in more than 3 dimensions

I have watched lectures upto Week3.

In regression, we plot the x and y co-ordinates on a plane and try to draw an imaginary line that reduces the aggregate of spatial distance between the line and the points. This imaginary line is called the boundary. In case of a binary valued output, the plane would be divided into two halves. In case of a real valued output, there can be many boundaries and they can even take different shapes.

Am I right with my conceptual understanding? If I am right, then
• How to visualize in a geometric form if x has lot of features/dimensions? From my limited reading on ML, I have seen that each feature of x could be visualized for y. But is there a more effective way?
• This question may be more ambiguous but is there a way to comprehend the details in a non-geometric form?
• Is the geometric examples given is just a way to understand the problem or is it the only way to solve ML problems?
__________________
Its better to look dumb and be clear rather than look smart and be unclear.

 Tags dimensions, spatial, visualization

 Thread Tools Display Modes Hybrid Mode

 Posting Rules You may not post new threads You may not post replies You may not post attachments You may not edit your posts BB code is On Smilies are On [IMG] code is On HTML code is Off Forum Rules
 Forum Jump User Control Panel Private Messages Subscriptions Who's Online Search Forums Forums Home General     General Discussion of Machine Learning     Free Additional Material         Dynamic e-Chapters         Dynamic e-Appendices Course Discussions     Online LFD course         General comments on the course         Homework 1         Homework 2         Homework 3         Homework 4         Homework 5         Homework 6         Homework 7         Homework 8         The Final         Create New Homework Problems Book Feedback - Learning From Data     General comments on the book     Chapter 1 - The Learning Problem     Chapter 2 - Training versus Testing     Chapter 3 - The Linear Model     Chapter 4 - Overfitting     Chapter 5 - Three Learning Principles     e-Chapter 6 - Similarity Based Methods     e-Chapter 7 - Neural Networks     e-Chapter 8 - Support Vector Machines     e-Chapter 9 - Learning Aides     Appendix and Notation     e-Appendices

All times are GMT -7. The time now is 07:22 PM.